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中文摘要：
服务环境中的动态性会对故障诊断算法性能造成影响．为了降低这种影响，分析了服务环境中的动态性，提出多层管理模型建模服务系统：二分贝叶斯网络建立依赖模型和二元对称信道建模噪声．针对故障自动修复机制导致的动态故障集环境，在故障持续时间统计的基础上修正当前窗口内先验故障概率；针对动态模型环境，基于当前窗口内原始模型和观察症状时间建立期望模型．仿真结果显示，算法可以有效地诊断动态环境下的互联网服务故障．
英文摘要：
Dynamic changes in service environment will affect fault diagnosis algorithm. In order to reduce the impact, challenges of fault diagnosis in dynamic environment are analyzed in this paper. Multi-layer management model is presented to model the service system, Bipartite Bayesian network is chosen to model the dependency relationship and binary symmetric channel is chosen to model noises. To deal with the dynamic fault set caused by fault recovery mechanism, prior fault probability is modified based on fault persistent time statistic; To deal with the dynamic model, expected model is built based on the time of observing symptoms and original models in current window. Simulation results show that this fault diagnosis algorithm is efficient in dynamic Interact service environment.
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